tutorials

python scripts/tutorials/00_sim/spawn_prims.py python scripts/tutorials/00_sim/create_empty.py python scripts/tutorials/00_sim/launch_app.py

python scripts/tutorials/03_envs/create_cube_base_env.py --num_envs 8 python scripts/tutorials/03_envs/policy_inference_in_usd.py --checkpoint assets/Policies/Isaac-Velocity-Rough-H1-v0/policy.pt python scripts/tutorials/03_envs/policy_inference_with_keyboard.py --checkpoint assets/Policies/Isaac-Velocity-Rough-H1-v0/policy.pt

python scripts/tutorials/01_assets/run_rigid_object.py python scripts/tutorials/01_assets/run_articulation.py python scripts/tutorials/01_assets/run_deformable_object.py python scripts/tutorials/01_assets/run_tennis_ball.py python scripts/tutorials/04_sensors/add_sensors_on_robot.py --enable_cameras python scripts/tutorials/04_sensors/run_ray_caster.py python scripts/tutorials/04_sensors/run_ray_caster_camera.py

demos

python scripts/demos/arms.py python scripts/demos/multi_asset.py python scripts/demos/multi_asset_more.py

benchmark

python scripts/benchmarks/benchmark_rlgames.py --task=Isaac-Cartpole-RGB-Camera-Direct-v0 --headless --enable_cameras python scripts/benchmarks/benchmark_rlgames.py --task=Isaac-Cartpole-RGB-Camera-Direct-v0 --headless --enable_cameras --num_envs 128

Tests

python source/isaaclab/test/assets/check_ridgeback_franka.py

Manage-Based Ant

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Ant-v0 --num_envs 32

Manage-Based Humanoid

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Humanoid-v0 --num_envs 32

Manage-Based navigation

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Navigation-Flat-Anymal-C-v0 --num_envs 32 Isaac-Navigation-Flat-Anymal-C-Play-v0

Manage-Based locomotion velocity

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Flat-Spot-v0 --num_envs 32

Manage-Based Flat-H1

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Flat-H1-v0 --headless --video

Manage-Based Rough-H1

Observation Manager: contains 1 groups. +----------------------------------------------------------+ | Active Observation Terms in Group: 'policy' (shape: (256,)) | +-----------+--------------------------------+-------------+ | Index | Name | Shape | +-----------+--------------------------------+-------------+ | 0 | base_lin_vel | (3,) | | 1 | base_ang_vel | (3,) | | 2 | projected_gravity | (3,) | | 3 | velocity_commands | (3,) | | 4 | joint_pos | (19,) | | 5 | joint_vel | (19,) | | 6 | actions | (19,) | | 7 | height_scan | (187,) | +-----------+--------------------------------+-------------+

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Rough-H1-v0 --headless --video python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-Velocity-Rough-H1-Play-v0

quadcopter env set

python scripts/my_test/quadcopter_camera.py python scripts/demos/quadcopter.py python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-Franka-Cabinet-Direct-v0

Cartpole

python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-Cartpole-Direct-v0 python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-Cartpole-RGB-Camera-Direct-v0 --headless --enable_cameras --video --num_envs 512 python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Cartpole-Depth-Camera-Direct-v0 --headless --enable_cameras --num_envs 32

python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-Cartpole-RGB-ResNet18-v0 --headless --enable_cameras --video python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-Cartpole-RGB-TheiaTiny-v0 --headless --enable_cameras --video

python scripts/reinforcement_learning/rl_games/play.py --task=Isaac-Cartpole-RGB-Camera-Direct-v0 --checkpoint logs/rl_games/cartpole_camera_direct/2024-06-06_11-01-07/nn/cartpole_camera_direct.pth

python -m tensorboard.main --logdir logs/rl_games/cartpole_camera_direct

Jetbot

python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-Jetbot-Direct-v0

无人机

python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-Quadcopter-Direct-v0 python scripts/reinforcement_learning/rl_games/play.py --task=Isaac-Quadcopter-Direct-v0 python -m tensorboard.main --logdir logs/rl_games/quadcopter_direct/2024-06-05_19-17-12 python -m tensorboard.main --logdir logs/rsl_rl/quadcopter_direct/2024-06-20_15-53-02

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Quadcopter-Direct-v0 --headless

python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-Quadcopter-Direct-v0 --checkpoint=model_11600.pt --num_envs=2 python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-Quadcopter-Direct-play-v0 --headless --checkpoint model_11600.pt

python scripts/reinforcement_learning/sb3/train.py --task=Isaac-Quadcopter-Direct-v0 --headless

UAV

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-UAV-Direct-v0 --num_envs 8 python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-UAV-PTZ-Direct-v0 --num_envs 8 python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-UAV-Control-Direct-v0 --num_envs 8192 --headless python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-UAV-Control-Direct-v0 --num_envs 8192 --headless --resume True --load_run 2024-12-12_13-27-40 --checkpoint model_5000.pt

python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-UAV-Control-Direct-v0 --num_envs 8 --load_run policy --checkpoint model_9000.pt

python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-PTZ-Control-Direct-v0 --num_envs 2 --headless --enable_cameras --checkpoint model_9000.pt

python scripts/reinforcement_learning/rsl_rl/play_jit.py --task=Isaac-PTZ-Control-Direct-v0 --num_envs 2 --headless --enable_cameras --checkpoint policy.pt

python scripts/reinforcement_learning/rsl_rl/play_onnx.py --task=Isaac-PTZ-Control-Direct-v0 --num_envs 2 --headless --enable_cameras --checkpoint policy.onnx

python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-UAV-Fly-v0 --num_envs 4 --enable_cameras --headless --livestream 1

PTZ-UAV

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-PTZ-Control-Direct-v0 --num_envs 256 --enable_cameras --headless --video

python -m torch.distributed.run --nnodes=1 --nproc_per_node=3 scripts/reinforcement_learning/skrl/train.py --task=Isaac-PTZ-Control-Direct-v0 --num_envs 2048 --enable_cameras --headless --distributed

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-PTZ-Control-Direct-v0 --num_envs 256 --enable_cameras --headless --resume True python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-PTZ-Control-Direct-v0 --num_envs 8 --enable_cameras

Kaya

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Kaya-Direct-v0 --num_envs 4096 --headless python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Kaya-Tennis-v0 --num_envs 4096 --headless python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-Kaya-Tennis-Play-v0 --num_envs 2 python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Kaya-VA-v0 --num_envs 256 --enable_cameras --headless python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Kaya-VA-v0 --num_envs 128 --enable_cameras --video --video_length 1000 --video_interval 50000 --headless

python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Kaya-Tennis-v1 --num_envs 2048 --algorithm TD3 --headless python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Kaya-Tennis-v1 --num_envs 1024 --video --video_length 1000 --video_interval 200 --algorithm TD3 --headless python -m tensorboard.main --logdir logs/skrl/kaya_tennis_td3/2025-02-12_17-06-06_td3_torch

Agilex Robotics

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-ScoutMini-Direct-v0 --num_envs 4096 --headless

python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-ScoutMini-AV-v0 --num_envs 4096 --enable_cameras --headless python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-ScoutMini-AV-v0 --num_envs 16 --enable_cameras

python scripts/reinforcement_learning/skrl/train.py --task=Isaac-ScoutMini-AV-v0 --num_envs 512 --enable_cameras --livestream 2 python scripts/reinforcement_learning/skrl/train.py --task=Isaac-ScoutMini-AV-Yolo-v0 --num_envs 128 --enable_cameras --livestream 2

python -m tensorboard.main --logdir logs/skrl/scout_mini_va/2025-03-10_12-14-16_ppo_torch

Multi GPU Train

python -m torch.distributed.run --nnodes=1 --nproc_per_node=3 scripts/reinforcement_learning/skrl/train.py --task=Isaac-Kaya-VA-v0 --num_envs 4096 --enable_cameras --headless --distributed

python -m torch.distributed.run --nnodes=1 --nproc_per_node=3 scripts/reinforcement_learning/skrl/train.py --task=Isaac-Kaya-VA-v0 --num_envs 4096 --enable_cameras --video --video_length 1000 --video_interval 50000 --headless --distributed

python -m tensorboard.main --logdir logs/skrl/kaya_va_direct/2025-01-22_16-27-36_ppo_torch python -m tensorboard.main --logdir logs/rsl_rl/kaya_tennis/2025-01-22_22-03-52

Duck

Direct Duck

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Flat-Duck-Direct-v0 --num_envs 4096 --headless python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Flat-Duck-Direct-v0 --num_envs 4096 --headless --resume True python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-Velocity-Flat-Duck-Direct-v0 --num_envs 4 --headless --livestream 1

Managed Duck

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Flat-Duck-v0 --num_envs 4096 --headless python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-Velocity-Flat-Duck-Play-v0 python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-Velocity-Flat-Duck-Play-v0 --headless --livestream 1

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Flat-BDX-v0 --num_envs 4096 --headless python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-Velocity-Flat-BDX-Play-v0 python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-Velocity-Flat-BDX-Play-v0 --headless --livestream 1 python -m tensorboard.main --logdir logs/rsl_rl/bdx_flat/2025-01-17_20-30-01 python source/isaaclab_tasks/isaaclab_tasks/direct/humanoid_amp/motions/motion_viewer.py --file humanoid_walk.npz --render-scene True

teddy_bear

python scripts/environments/state_machine/lift_teddy_bear.py --num_envs 4

Manage-Based 无人机

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Quadcopter-v0 --num_envs 32

平滑控制版本

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Quadcopter-Smooth-v0 --headless

带IMU

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Quadcopter-IMU-v0 --headless

带摄像头

python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-Quadcopter-RGB-Camera-Direct-v0 --headless --enable_cameras --video python -m tensorboard.main --logdir logs/rl_games/quadcopter_direct_camera/2024-06-09_07-56-25

python scripts/reinforcement_learning/rl_games/play.py --task=Isaac-Quadcopter-RGB-Camera-Direct-v0 --checkpoint logs\rl_games\quadcopter_direct_camera\2024-06-12_09-46-08\nn\quadcopter_direct_camera.pth

python scripts/reinforcement_learning/sb3/train.py --task=Isaac-Quadcopter-Direct-v0

视觉避障 1.0

python scripts/reinforcement_learning/sb3/train.py --task=Isaac-Quadcopter-RGB-Camera-Direct-v0 --headless --enable_cameras python -m tensorboard.main --logdir logs/sb3/Isaac-Quadcopter-Direct-v0/2024-06-24_11-45-43

视觉避障 2.0

python scripts/reinforcement_learning/sb3/train.py --task=Isaac-Quadcopter-Vision-OA-v0 --enable_cameras python scripts/reinforcement_learning/sb3/train.py --task=Isaac-Quadcopter-Vision-OA-v0 --headless --enable_cameras --video

python -m tensorboard.main --logdir logs/sb3/Isaac-Quadcopter-Direct-v0/2024-06-24_11-45-43 python -m tensorboard.main --logdir logs/sb3/Isaac-Quadcopter-RGB-Camera-Direct-v0/2024-06-24_16-35-21

视觉避障 3.0

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Quadcopter-Vision-Depth-v0 --headless --enable_cameras

人形机器人

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Humanoid-Direct-v0

SLAM

python scripts/standalone/lidar_imu_pub/main.py --checkpoint assets/Policies/Isaac-Velocity-Rough-H1-v0/policy.pt

AMP

Humanoid-AMP

python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Humanoid-AMP-Dance-Direct-v0 --headless --algorithm AMP python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Humanoid-AMP-Run-Direct-v0 --headless --algorithm AMP python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Humanoid-AMP-Walk-Direct-v0 --headless --algorithm AMP python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Humanoid-AMP-Dance-Direct-v0 --headless --algorithm AMP --video --video_length 200 --video_interval 10000 python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Humanoid-AMP-Walk-Rough-v0 --headless --algorithm AMP --num_envs 512

python scripts/reinforcement_learning/skrl/play.py --task=Isaac-Humanoid-AMP-Dance-Direct-v0 --num_envs 32 --algorithm AMP --real-time python scripts/reinforcement_learning/skrl/play.py --task=Isaac-Humanoid-AMP-Run-Direct-v0 --num_envs 32 --algorithm AMP --real-time python scripts/reinforcement_learning/skrl/play.py --task=Isaac-Humanoid-AMP-Walk-Direct-v0 --num_envs 32 --algorithm AMP --real-time

python -m tensorboard.main --logdir logs/skrl/humanoid_amp_walk/2025-02-13_08-01-20_amp_torch

Test

Test contact_sensor

python source/isaaclab/test/sensors/test_contact_sensor.py

Test Imu sensor

python source/isaaclab/test/sensors/test_imu.py python source/isaaclab/test/sensors/check_imu_sensor.py python scripts/tutorials/06_ros/imu_sensor_to_ros.py

Test Camera

python scripts/tutorials/04_sensors/add_more_sensors_on_robot.py --enable_cameras

ROS

python scripts/tutorials/06_ros/tiled_camera.py --enable_cameras python scripts/tutorials/06_ros/tiled_camera_threading.py --enable_cameras python scripts/tutorials/06_ros/camera.py --enable_cameras

lifelong_slam

python .\source\standalone\lidar_slam\play.py --task=Isaac-Quadcopter-Direct-Lidar-v0 --load_run 2024-10-22_13-08-21 --checkpoint model_1000.pt

python scripts/standalone/lidar_imu_pub/main.py --checkpoint assets/Policies/Isaac-Velocity-Rough-H1-v0/policy.pt

ros2 bag record -o full_warehouse.bag /imu /point_cloud2

大模型机器人

python -m tensorboard.main --logdir logs/eureka/Isaac-Cartpole-Direct-v0/2024-12-05_11-22-51

修改意见

_isaac_sim\exts\omni.isaac.sensor\omni\isaac\sensor\scripts\menu.py data = json.load(open(d + "/" + file))

with open(d + "/" + file, 'r', encoding='utf-8') as f: data = json.load(f)

isaac sim 4.2 版本后： data = json.load(open(os.path.join(d, file)))

改为： with open(os.path.join(d, file), encoding='utf-8') as f: data = json.load(f)

如遇到： File "/root/anaconda3/envs/sx_isaaclab/lib/python3.10/site-packages/rsl_rl/utils/utils.py", line 83, in store_code_state f.write(content) UnicodeEncodeError: 'ascii' codec can't encode characters in position 4947-4949: ordinal not in range(128)

将这个代码 with open(diff_file_name, "x") as f: content = f"--- git status ---\n{repo.git.status()} \n\n\n--- git diff ---\n{repo.git.diff(t)}" f.write(content) 修改为： with open(diff_file_name, "x", encoding='utf-8') as f: content = f"--- git status ---\n{repo.git.status()} \n\n\n--- git diff ---\n{repo.git.diff(t)}" f.write(content)

编队单点导航

python scripts/reinforcement_learning/sb3/train.py --task=Isaac-Quadcopter-Form-v0 --headless python scripts/reinforcement_learning/sb3/train_form_td3.py --task=Isaac-Quadcopter-Form-v0 --headless python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-Quadcopter-Form-v0 --headless python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Quadcopter-Form-v0 --headless python scripts/reinforcement_learning/skrl/train.py --task=Isaac-Quadcopter-Form-v0 --headless --max_iterations 1000000

python scripts/reinforcement_learning/rsl_rl/play.py --task=Isaac-Quadcopter-Form-Play-v0 --checkpoint model_10000.pt

python -m tensorboard.main --logdir logs/skrl/quadcopter_form_direct/2024-07-25_09-13-04 python -m tensorboard.main --logdir logs/rsl_rl/quadcopter_form_direct/2024-07-31_20-04-06

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Quadcopter-Form-v0 --headless --resume True --load_run 2024-07-31_20-04-06 --checkpoint model_8600.pt

编队飞路径

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Quadcopter-Form-Path-v0 --headless

python scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Quadcopter-Form-Path-v0 --headless --resume True --load_run 2024-07-31_20-04-06 --checkpoint model_8600.pt

更新Isaac Lab

.\isaaclab.bat --install

pip install -i https://pypi.tuna.tsinghua.edu.cn/simple transformers pip install -i https://pypi.tuna.tsinghua.edu.cn/simple einops

单独升级 rsl_rl pip install git+https://github.com/leggedrobotics/rsl_rl.git

单独升级 skrl ./isaaclab.bat -p -m pip show skrl ./isaaclab.bat -p -m pip install -i https://pypi.tuna.tsinghua.edu.cn/simple --upgrade skrl ./isaaclab.sh -p -m pip install git+https://github.com/Toni-SM/skrl.git@develop ./isaaclab.sh -p -m pip install git+https://gitee.com/shaoxiang/skrl.git@develop .\isaaclab.bat -p -m pip install git+https://github.com/Toni-SM/skrl.git@develop .\isaaclab.bat -p -m pip install git+https://gitee.com/shaoxiang/skrl.git@develop

单独升级 stable_baselines3 pip install -i https://pypi.tuna.tsinghua.edu.cn/simple stable-baselines3 pip install git+https://github.com/DLR-RM/stable-baselines3

单独升级 robomimic sudo apt install cmake build-essential ./isaaclab.sh -p -m pip install git+https://gitee.com/shaoxiang/robomimic

asserts error

将目录替换成你自己的下载的即可

.\isaac-sim.bat --/persistent/isaac/asset_root/default="D:\omniverse\Downloads\Assets\Isaac\4.2"

如果pytorch出了问题

pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

pip install torch==2.4.0 torchvision==0.19.0 --index-url https://download.pytorch.org/whl/cu118 或者： pip install torch==2.4.0+cu118 torchvision==0.19.0+cu118 -f https://download.pytorch.org/whl/torch

pip install torch==2.5.1+cu121 --use-deprecated=legacy-resolver --no-cache-dir -f https://mirrors.aliyun.com/pytorch-wheels/cu121

YOLO

pip install -i https://pypi.tuna.tsinghua.edu.cn/simple ultralytics --no-deps pip install -i https://pypi.tuna.tsinghua.edu.cn/simple onnxruntime-gpu --no-deps

Tips

1、添加可变形物体，核心要注意 replicate_physics 为 False 2、contact sensor 使用注意，如果使用 filter_prim_paths_expr 只保留与某些特定的物体之间碰撞，那么读取碰撞数值时应该使用force_matrix_w。 net_forces_w 报告总的净法向力，过滤后的力位于单独的属性 force_matrix_w 3、特权信息 observations = {"policy": obs, "critic": states}

人形机器人动捕数据播放

git clone https://hf-mirror.com/datasets/unitreerobotics/LAFAN1_Retargeting_Dataset

将目录替换成你自己的下载的即可

.\isaac-sim.bat --/persistent/isaac/asset_root/default="D:\omniverse\Downloads\Assets\Isaac\4.2" ./isaac-sim.sh --/persistent/isaac/asset_root/default="/home/ai/omniverse/Downloads/Isaac/4.2"

./isaac-sim.sh --/persistent/isaac/asset_root/default="/home/dell/omniverse/Downloads/Assets/Isaac/4.2"

isaac lab 安装相关

软链接到 _isaac_sim

ln -s /home/dell/.local/share/ov/pkg/isaac-sim-4.2.0 _isaac_sim
ln -s /home/ai/omniverse/pkg/isaac-sim-4.5.0 _isaac_sim

cmd需要管理员权限
mklink /D _isaac_sim D:\OMNIVERSE\pkg\isaac-sim-4.5.0

创建 conda env

.\isaaclab.bat --conda my_labv2
conda activate my_labv2

安装 isaac lab

.\isaaclab.bat --install

tips

anaconda unbuntu install

wget -c 'https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2024.10-1-Linux-x86_64.sh' -P ~/Downloads --user-agent="Mozilla/5.0 (X11;U;Linux i686;en-US;rv:1.9.0.3) Geco/2008092416 Firefox/3.0.3"

or

wget https://repo.anaconda.com/archive/Anaconda3-2024.10-1-Linux-x86_64.sh

bash Anaconda3-2024.10-1-Linux-x86_64.sh

conda 换源

channels:
  - https://repo.anaconda.com/pkgs/main
  - https://repo.anaconda.com/pkgs/r

channels:
  - defaults
show_channel_urls: true
default_channels:
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
custom_channels:
  conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud

conda remove env

conda env remove --name <environment_name>

ROS 配置，使用内部Isaac Sim ROS

export isaac_sim_package_path=$HOME/omniverse/isaac-sim-4.5.0
export RMW_IMPLEMENTATION=rmw_fastrtps_cpp
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$isaac_sim_package_path/exts/isaacsim.ros2.bridge/humble/lib

`GLIBCXX_3.4.29' not found

[ERROR] [1740746501.997882954] [rcl]: Error getting RMW implementation identifier / RMW implementation not installed (expected identifier of 'rmw_fastrtps_cpp'), with error message 'failed to load shared library 'librmw_fastrtps_cpp.so' due to dlopen error: /home/dell/anaconda3/envs/isaac_labv2/bin/../lib/libstdc++.so.6: version `GLIBCXX_3.4.30' not found (required by /opt/ros/humble/lib/libfastrtps.so.2.6), at ./src/shared_library.c:99, at ./src/functions.cpp:65', exiting with 1., at ./src/rcl/rmw_implementation_identifier_check.c:139

当你尝试在Linux上运行Python程序或启动Anaconda环境时，可能会遇到ImportError: /home/anaconda3/lib/libstdc++.so.6: versionGLIBCXX_3.4.29’ not found的错误。这个错误通常表明你的系统或Anaconda环境中的libstdc++.so.6`库的版本与Python或其某个库所需的版本不兼容。

sudo find / -name libstdc++.so.6

strings /home/dell/anaconda3/envs/isaac_labv2/lib/libstdc++.so.6 | grep GLIBCXX

ln -sf /home/dell/anaconda3/lib/libstdc++.so.6 /home/dell/anaconda3/envs/isaac_labv2/lib/libstdc++.so.6

isaac sim reset user To run Isaac Sim with a fresh config, use the --reset-user flag. This flag can be entered in the Extra Args section of the Isaac Sim App Selector or when running Isaac Sim in command line.

.\isaac-sim.bat --reset-user

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